Challenging common climate assumptions

Written by Pablo Villaizan Marin, Engineering project manager

Reflections from verifying LCAs and working with real product data

When companies start working with climate footprints across their products, materials, and processes we can see that teams genuinely want to make better decisions, reduce impact, and move in the right direction. But we often see how choices aimed at reducing environmental impact can be made quickly or intuitively, based on what feels right in the moment. A material may be selected because it looks more sustainable (even when the underlying climate footprint has not yet been documented), or a process may be adjusted with the expectation that it will automatically lead to lower emissions.

What initially appears to be a clear improvement can turn out to be marginal, or it can shift the impact somewhere else in the system entirely. Maybe not because the idea was wrong, but because the system itself is more interconnected than the initial assumption suggests.

In that space, assumptions naturally emerge. They help move things forward. But they also shape the direction of decisions in ways that are not always visible at first.

We often come across recurring ideas for climate impact that seem straightforward on the surface. That bio-based materials are inherently better. That recycled content always leads to lower impact. That using less plastic automatically reduces emissions. These statements will first need to be checked, and furthermore they become risky when treated as conclusions, being the reality that their validity will also depend heavily on context too.

Where and how materials are sourced, the energy mix used in production, transportation methods, and what happens at end-of-life all play a critical role in shaping the final environmental outcome. Two products that appear similar can therefore have very different footprints once these factors are properly accounted for.

Working in LCA verifications I have also seen how this service could become particularly valuable. Not as a way of simply confirming whether something is right or wrong, but as a process that strengthens understanding. When we go through an LCA together, we don’t only look at results. We look at how those results were built: what assumptions were made, what data was available, and how the system was defined. And just as importantly, we create space to question and refine those assumptions.

Often, this is where the most meaningful progress happens. Not in validating expectations, but in adjusting them based on what the data shows. As understanding deepens, the conversation shifts away from simplified notions of “better or worse” and towards a more precise view of what is changing, where, and by how much.

Over time, we have seen that data and evaluations does not make decisions more complicated. It makes them clearer. It helps focus attention on the areas that truly drive impact, avoids changes that look good on paper but deliver limited improvement, and supports the development of claims that can stand up to scrutiny.

Working with climate impact is not about removing assumptions entirely. That is rarely possible. It is about becoming aware of them, testing them, and understanding what they imply before acting on them. When that happens, decisions tend to become more grounded, more transparent, and ultimately more effective.